Video/image processing in a low light environment introduces a tension or tradeoff between noise and motion. The low number of photons in the low light environment produces noisy images, especially noisy color images. Increasing the exposure time of a camera to allow collection of more photons reduces noise, but large exposure time values could increase motion blur due to potential object motion within the exposure period. Several solutions have been proposed to remedy color imaging in a low light environment, such as a 0 lux environment. For example, a variety of external light illuminators have been proposed, such as monochrome, (infrared) IR, or white light illuminators.
There are a number of problems with typical external illuminators. For example, the IR illuminators do not enable the detection of color images. Although white light illuminators combined with color image sensors allow color detection, they suffer from a very low optical efficiency due to wastage of majority of the light collected by the camera lens in the color image sensors. This low optical efficiency is particularly undesirable in situations where the electrical power available to the illuminator is limited. For instance, the illuminator power in a network camera is limited by the IEEE Power over Ethernet specifications and therefore the brightness of the external illuminators would be limited. Moreover, the illumination spectrum and intensity of IR and white light illuminators are not adaptive to scene requirements.
Virtually, all color cameras are equipped with a Bayer filter to detect color. A Bayer filter is a color filter array for arranging red, green, and blue color filters on a grid of photo sensors. Typically, the filter array has more green filters than red and blue. For example, a Bayer filter array could have 50% green, 25% red and 25% blue filters. This arrangement of color filters creates a color image from, for example, digital cameras. However, by its nature, each pixel with a color filter allows only about 20% of neutrally colored light entering the camera to be detected. This is mainly because a filter of a given primary color is designed to block other primary colors from being detected. For instance, a red filter blocks green and blue light; a green filter blocks red and blue light; and a blue filter blocks red and green light. This low efficiency of the light detection becomes very significant in a low (or zero lux) light environment. Moreover, due to low light efficiency, the color images appear noisy. This is because the signal to noise ratio of color images decrease with decreasing light levels. Additionally, Bayer filter based color sensors may exhibit substantial color signal crosstalk because of leakage between the neighboring pixels. This is especially a problem in cameras that use large apertures (small F/#) due to the high cone angle of the light entering the pixels. Further, Bayer filter based color imagers do not detect all three (red, green, blue) colors at each pixel. This drawback is typically compensated by using an image processing procedure called as demosaicing, which leads to degradation in spatial resolution.
Accordingly, there is a need for an enhanced video image processing technique that decreases noise and color artifacts, while minimizing motion blur and resolution degradation, without requiring a complex architecture, large memory, and/or high bandwidth.